Deep Learning–Based Full-Waveform Inversion of GPR Snowpack Data

This dataset contains the simulation files, labeled data, deep learning codes, and inversion results used in the study “Deep Learning–Based Full-Waveform Dual Parameter Inversion of Ground Penetrating Radar (GPR) Snowpack Data for Liquid Water Content Mapping.” The repository includes input files for gprMax simulations, processed radar B-scans, ground-truth labeled data for supervised learning, synthetic and field inversion results, and Python codes implementing ViT–BiLSTM and Xception–ASPP deep learning architectures. The data support the reproducibility of the study and enable further research in snowpack monitoring, cryosphere hydrology, and electromagnetic full-waveform inversion.